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Argument and Counter-Argument Generation: A Critical Survey

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Natural Language Processing and Information Systems (NLDB 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13913))

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Abstract

Argument Generation (AG) is becoming an increasingly active research topic in Natural Language Processing (NLP), and a large variety of terms has been used to highlight different aspects and methods of AG such as argument construction, argument retrieval, argument synthesis and argument summarization, producing a vast literature. This article aims to draw a comprehensive picture of the literature concerning argument generation and counter-argument generation (CAG). Despite the increasing interest on this topic, no attempt has been made yet to critically review the diverse and rich literature in AG and CAG. By confronting works from the relevant subareas of NLP, we provide a holistic vision that is essential for future works aiming to produce understandable, convincing and ethically sound arguments and counter-arguments.

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Notes

  1. 1.

    https://www.research.ibm.com/artificial-intelligence/project-debater/.

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Acknowledgements

This work has been partially supported by the ANR project ATTENTION (ANR21-CE23-0037) and the French government through the 3IA Côte d’Azur Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002.

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Authors and Affiliations

  1. Université Côte d’Azur, CNRS, Inria, I3S, Sophia Antipolis, France

    Xiaoou Wang, Elena Cabrio & Serena Villata

Authors
  1. Xiaoou Wang
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  2. Elena Cabrio
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  3. Serena Villata
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Corresponding author

Correspondence to Xiaoou Wang .

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Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

  2. University of Derby, Derby, UK

    Farid Meziane

  3. Oakland University, Rochester, NY, USA

    Vijayan Sugumaran

  4. University of Derby, Derby, UK

    Warren Manning

  5. University of Derby, Derby, UK

    Stephan Reiff-Marganiec

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Wang, X., Cabrio, E., Villata, S. (2023). Argument and Counter-Argument Generation: A Critical Survey. In: Métais, E., Meziane, F., Sugumaran, V., Manning, W., Reiff-Marganiec, S. (eds) Natural Language Processing and Information Systems. NLDB 2023. Lecture Notes in Computer Science, vol 13913. Springer, Cham. https://doi.org/10.1007/978-3-031-35320-8_37

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  • DOI: https://doi.org/10.1007/978-3-031-35320-8_37

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  • Online ISBN: 978-3-031-35320-8

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